My program need to be have a function that reads data from a csv file ("all.csv") and extract all the data pertaining to 'Virginia' (extract each row that has 'Virginia in it). Then write the extracted data to another csv file named "Virginia.csv" The program runs without error, however, when I open the "Virginia.csv" file, nothing is written in it, it is blank. My guess is that the issue is with my nested for loop, but I am not entirely sure what is causing the issue.
Here is the data within the all.csv file:
https://raw.githubusercontent.com/nytimes/covid-19-data/master/us-counties.csv
Here is my code:
import csv
input_file = 'all.csv'
output_file = 'Virginia.csv'
state = 'Virginia'
mylist = []
def extract_records_for_state (input_file, output_file, state):
with open(input_file, 'r') as infile:
contents = infile.readlines()
with open(output_file, 'w') as outfile:
writer = csv.writer(outfile)
for row in range(len(contents)):
contents[row] = contents[row].split(',') #split elements
for row in range(len(contents)):
for word in range(len(contents[row])):
if contents[row][2] == state:
writer.writerow(row)
extract_records_for_state(input_file,output_file,state)
CodePudding user response：
I ran your code and it gave me an error
Traceback (most recent call last): File "c:\Users\Dolimight\Desktop\Stack Overflow\Geraldo\main.py", line 27, in extract_records_for_state(input_file, output_file, state) File "c:\Users\Dolimight\Desktop\Stack Overflow\Geraldo\main.py", line 24, in extract_records_for_state writer.writerow(row) _csv.Error: iterable expected, not int,
I fixed the error by putting the contents of the row [contents[row]] into the writerow() function and ran it again and the data showed up in Virginia.csv. It gave me duplicates so I also removed the word for-loop.
import csv
input_file = 'all.csv'
output_file = 'Virginia.csv'
state = 'Virginia'
mylist = []
def extract_records_for_state(input_file, output_file, state):
with open(input_file, 'r') as infile:
contents = infile.readlines()
with open(output_file, 'w') as outfile:
writer = csv.writer(outfile)
for row in range(len(contents)):
contents[row] = contents[row].split(',') # split elements
print(contents)
for row in range(len(contents)):
if contents[row][2] == state:
writer.writerow(contents[row]) # this is what I changed
extract_records_for_state(input_file, output_file, state)
CodePudding user response：
You have two errors. The first is that you try to write the row index at writer.writerow(row) - the row is contents[row]. The second is that you leave the newline in the final column on read but don't strip it on write. Instead you could leverage the csv module more fully. Let the reader parse the rows. And instead of reading into a list, which uses a fair amount of memory, filter and write row by row.
import csv
input_file = 'all.csv'
output_file = 'Virginia.csv'
state = 'Virginia'
mylist = []
def extract_records_for_state (input_file, output_file, state):
with open(input_file, 'r', newline='') as infile, \
open(output_file, 'w', newline="") as outfile:
reader = csv.reader(infile)
writer = csv.writer(outfile)
# add header
writer.writerow(next(reader))
# filter for state
writer.writerows(row for row in reader if row[2] == state)
extract_records_for_state(input_file,output_file,state)
CodePudding user response：
Looking at your code two things jump out at me:
- I see a bunch of nested statements (logic)
- I see you reading a CSV as plain text, then interpreting it as CSV yourself (
contents[row] = contents[row].split(',')).
I recommend two things:
- break up logic into distinct chunks: all that nesting can be hard to interpret and debug; do one thing, prove that works; do another thing, prove that works; etc...
- use the CSV API to its fullest: use it to both read and write your CSVs
I don't want to try and replicate/fix your code, instead I'm offering this general approach to achieve those two goals:
import csv
# Read in
all_rows = []
with open('all.csv', 'r', newline='') as f:
reader = csv.reader(f)
next(reader) # discard header (I didn't see you keep it)
for row in reader:
all_rows.append(row)
# Process
filtered_rows = []
for row in all_rows:
if row[2] == 'Virginia':
filtered_rows.append(row)
# Write out
with open('filtered.csv', 'w', newline='') as f:
writer = csv.writer(f)
writer.writerows(filtered_rows)
Once you understand both the logic and the API of those discrete steps, you can move on (advance) to composing something more complex, like the following which reads a row, decides if it should be written, and if so, writes it:
import csv
with open('filtered.csv', 'w', newline='') as f_out:
writer = csv.writer(f_out)
with open('all.csv', 'r', newline='') as f_in:
reader = csv.reader(f_in)
next(reader) # discard header
for row in reader:
if row[2] == 'Virginia':
writer.writerow(row)
Using either of those two pieces of code on this (really scaled-down) sample of all.csv:
date,county,state,fips,cases,deaths
2020-03-09,Fairfax,Virginia,51059,4,0
2020-03-09,Virginia Beach city,Virginia,51810,1,0
2020-03-09,Chelan,Washington,53007,1,1
2020-03-09,Clark,Washington,53011,1,0
gets me a filtered.csv that looks like:
2020-03-09,Fairfax,Virginia,51059,4,0
2020-03-09,Virginia Beach city,Virginia,51810,1,0
Given the size of this dataset, the second approach of write-on-demand-inside-the-read-loop is both faster (about 5x faster on my machine) and uses significantly less memory (about 40x less on my machine, because there's no intermediate storage with all_rows).
But, please take the time to run both, read them carefully, and see how each works the way it does.